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Chi ha portato Internet in Africa? Prima di una rete di computer bisogna costruire reti di persone; l\u27Italia l\u27ha fatto
No full textQuando parliamo di Internet parliamo di qualcosa che riguarda tutti, si tutti anche i paesi pi? sfortunati. Oltre il 70% degli abitanti del contenente africano non ? ancora connesso. Quasi un miliardo di persone sconnesse, in Italia si direbbe fuori dal futuro! Un divide, quello digitale, che rischia di aumentare le diseguaglianze gi? tristemente note in quel continente. Nel 1992 il CNUCE, istituto del CNR di Pisa che da poco aveva connesso l?Italia ad Internet, si lanciava nell?avventura di portare quella rete in oltre 15 paesi del continente africano: con un finanziamento di circa un milione di dollari del governo Italiano, sotto l?egida dell?UNESCO, si dovevano porre le basi per favorire i primi collegamenti. La nostra missione consisteva nell?acquisire e trasferire attrezzature, nel fornire assistenza tecnica per realizzare le connessioni di rete in numerose universit? africane e soprattutto nel formare gli amici e colleghi di quei paesi, sia attraverso numerosi corsi per operatori di rete tenuti in loco, sia organizzando la loro partecipazione ai principali incontri internazionali sulle reti. Il progetto si chiamava RINAF (Regional Informatic Networks for Africa), e segn? indubbiamente l?inizio della mia avventura africana, oltre all?entusiasmante impatto con il mondo di Internet
Liste di autorit? per l?indicizzazione e la conservazione digitale dell?archivio del CNUCE e della CGI
No full textThis paper aims to present a use case on the creation of integrated local authorityfiles referring to personal names of important Italian scientists and literates and organizationsto be used within the Science & Technology Digital Library (S&TDL) of the ItalianNational Research Council (CNR), and mined from more than 360 digitized documentsreporting the history of the Centro Nazionale Universitario di Calcolo Elettronico (CNUCE)of CNR and of the Commissione Generale per l?Informatica (CGI)
A Formal and Run-time Framework for the Adaptation of Local Behaviours to Match a Global Property
No full textWe address the problem of automatically identifying what local properties the agents of a Cyber Physical System have to satisfy to guarantee a global required property . To enrich the picture, we consider properties where, besides qualitative requirements on the actions to be performed, we assume a weight associated with them: quantitative properties are specied through a weighted modal-logic. We propose both a formal machinery based on a Quantitative Partial Model Checking function on contexts, and a run-time machinery that algorithmically tries to check if the local behaviours proposed by the agents satisfy . The proposed approach can be seen as a run-time decomposition, privacy sensitive in the sense agents do not have to disclose their full behaviour
Automated adaptation via quantitative partial model checking.
No full textWe propose a formal framework to model an automated adaptation protocol based on Quantitative Partial Model Checking (QPMC). An agent seeks the collaboration of a second agent to satisfy some (fixed) condition on the actions to be executed. The provided protocol allows the two agents to automatically agree by iteratively applying QPMC
Towards a Usage Control based Video Surveillance Framework
No full textThe increasing need for physical security in critical environment has led to a widespread of video surveillance systems. Effective video surveillance systems should be able to detect the presence of unauthorized people in the monitored environments while preserving the privacy of authorized ones. To this aim, our paper proposes the adoption of the usage control model in the video surveillance scenario to enforce security policies that continuously control whether a person holds the right to stay in a give space (e.g., a room) from the moment when this person enters that space. In some scenarios, a person is allowed to stay in the room only under some circumstances, which are described by the usage control policy. When the policy is violated an action is taken, e.g., the video camera placed in the room enables the registration. %recording the video stream captured by the video surveillance system is recorded. This paper presents the architecture of the proposed framework, provides an example of usage control policy in a real scenario, and describes the main details of our prototype implementation
Hypothesis Transfer Learning for Efficient Data Computing in Smart Cities Environments
No full textIt is commonly assumed that in a smart city there will be thousands of mostly mobile/wireless smart devices (e.g. sensors, smart-phones, etc.) that will continuously generate big amounts of data. Data will have to be collected and processed in order to extract knowledge out of it, to feed users\u27 and smart city applications. A typical approach to process such big amounts of data is to i) gather all the collected data on the cloud through wireless pervasive networks, and ii) perform data analysis operations exploiting machine learning techniques. However, according to many studies, this centralised cloud-based approach may not be sustainable from a networking point of view. The joint effect of data-intensive users\u27 multimedia applications and smart cities monitoring and control applications may result in severe network congestions making applications hardly usable. To cope with this problem, in this paper we propose a distributed machine learning approach that does not require to move data in a centralised cloud platform, but processes it directly where it is collected. Specifically, we exploit Hypothesis Transfer Learning (HTL) to build a distributed machine learning framework. In our framework we train a series of partial models, each \u27\u27residing\u27\u27 in a location where a subset of the dataset is generated. We then refine the partial models by exchanging them between locations, thus obtaining a unique complete model. Using an activity classification task on a reference dataset as a concrete example, we show that the classification accuracy of the HTL model is comparable with that of a model built out of the complete dataset, but the cost in term of network overhead is dramatically reduced. We then perform a sensitiveness analysis to characterise how the overhead depends on key parameters. It is also worth noticing that the HTL approach is suitable for applications dealing with privacy sensitive data, as data can stay where they are generated, and do not need to be transferred to third parties, i.e., to a cloud provider, to extract knowledge out of it
Google web searches and Wikipedia results: a measurement study.
No full textHow are users exposed to Wikipedia results, in return to their web searches? Where are such results positioned on the screen? In this study, we experimentally measure the ranking of Wikipedia pages on Google Italia
Special Section on Challenged Networks
No full textIt is our great pleasure to introduce this Special Section of the Journal, presenting advanced solutions for mobile challenged networks. The special section collects extended papers from the 9th ACM Workshop on Challenged Networks, CHANTS 2014. After a decade of research into this area, the subject of challenged networks is both generating solutions for practical applications, still remaining a fertile ground for innovative research in a broad area of topics. Indeed, the networking mechanisms devised for challenged networks (encompassing also the opportunistic and DTN networking paradigms) can support several novel research areas, such as Mobile Edge Computing, IoT, architectures for the Future Internet (such as 5G), community networks, network support for developing areas, just to mention a few. The papers in this special section provide a very significant sample of the dual nature of current research in challenged network (applied and fundamental), covering both practical solutions for fully exploiting their potential, as well as fundamental results. Specifically, the special section presents findings about the optimal use of mobile devices storage resources when local applications and opportunistic forwarding tasks compete for them; the development and test of a practical context-aware framework for Web-based deployment of DTN applications; the analysis of robustness of opportunistic networks under Sybil attacks